where \(l_k\in \mathbb {R}^{1\times C}\)  is the weight, \(f_k\in \mathbb {R}^{1\times C}\)  is the feature of k-th neighbor. Inspired by [1]}, [2]}, we use self-attention mechanism to learn weight of different neighboring points:
\(l_k = \sigma (\mathcal {G}(\Delta _{P_{k}}, f_k))\) 
